Emotion rating from short blog texts

Alastair J. Gill*, Darren Gergle, Robert M. French, Jon Oberlander

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations


Being able to automatically perceive a variety of emotions from text alone has potentially important applications in CMC and HCI that range from identifying mood from online posts to enabling dynamically adaptive interfaces. However, such ability has not been proven in human raters or computational systems. Here we examine the ability of naive raters of emotion to detect one of eight emotional categories from 50 and 200 word samples of real blog text. Using expert raters as a 'gold standard', naive-expert rater agreement increased with longer texts, and was high for ratings of joy, disgust, anger and anticipation, but low for acceptance and 'neutral' texts. We discuss these findings in light of theories of CMC and potential applications in HCI.

Original languageEnglish (US)
Title of host publication26th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings, CHI 2008
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Print)9781605580111
StatePublished - Jan 1 2008
Event26th Annual CHI Conference on Human Factors in Computing Systems, CHI 2008 - Florence, Italy
Duration: Apr 5 2008Apr 10 2008

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Other26th Annual CHI Conference on Human Factors in Computing Systems, CHI 2008


  • Affect
  • Computer-mediated communication
  • Emotion
  • Language

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design


Dive into the research topics of 'Emotion rating from short blog texts'. Together they form a unique fingerprint.

Cite this